A guide to artificial intelligence for cancer researchers

Nature reviews. Cancer, Journal Year: 2024, Volume and Issue: 24(6), P. 427 - 441

Published: May 16, 2024

Language: Английский

---

Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine

Pharmaceutics, Journal Year: 2024, Volume and Issue: 16(10), P. 1328 - 1328

Published: Oct. 14, 2024

Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep and other advanced computational methods. These innovations unlocked unprecedented opportunities the acceleration drug discovery delivery, optimization treatment regimens, improvement patient outcomes. AI is swiftly transforming industry, revolutionizing everything from development to personalized medicine, target identification validation, selection excipients, prediction synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While integration promises enhance efficiency, reduce costs, improve both medicines health, it also raises important questions regulatory point view. In this review article, we will present comprehensive overview AI's applications in covering areas such as discovery, safety, more. By analyzing current research trends case studies, aim shed light on transformative impact industry its broader implications healthcare.

Language: Английский

---

A future role for health applications of large language models depends on regulators enforcing safety standards

The Lancet Digital Health, Journal Year: 2024, Volume and Issue: 6(9), P. e662 - e672

Published: Aug. 23, 2024

Among the rapid integration of artificial intelligence in clinical settings, large language models (LLMs), such as Generative Pre-trained Transformer-4, have emerged multifaceted tools that potential for health-care delivery, diagnosis, and patient care. However, deployment LLMs raises substantial regulatory safety concerns. Due to their high output variability, poor inherent explainability, risk so-called AI hallucinations, LLM-based applications serve a medical purpose face challenges approval devices under US EU laws, including recently passed Artificial Intelligence Act. Despite unaddressed risks patients, misdiagnosis unverified advice, are available on market. The ambiguity surrounding these creates an urgent need frameworks accommodate unique capabilities limitations. Alongside development frameworks, existing regulations should be enforced. If regulators fear enforcing market dominated by supply or technology companies, consequences layperson harm will force belated action, damaging potentiality advice.

Language: Английский

---

The EU passes the AI Act and its implications for digital medicine are unclear

npj Digital Medicine, Journal Year: 2024, Volume and Issue: 7(1)

Published: May 22, 2024

On 13 March 2024, the much-anticipated AI Act was passed by EU parliament and will soon be adopted as law. It apply new requirements for developers deployers of AI-enabled digital health tools (DHTs), including a defined class high-risk systems general-purpose AI. Although text law is available, complete in all but final checks legal wording much still not known about how affect landscape beyond. The many aspects ambiguous, often high-level objectives are stated, with detail to come later associated guidance, standards, member state policy. also uncertain intersect pre-existing sector-specific legislation medical There future steps legislative process that can clarify ambiguity, guidelines, implementing laws, author remains optimistic get implementation right.

Language: Английский

---

Artificial intelligence in liver cancer — new tools for research and patient management

Nature Reviews Gastroenterology & Hepatology, Journal Year: 2024, Volume and Issue: 21(8), P. 585 - 599

Published: April 16, 2024

Language: Английский

---

Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions

Current Oncology, Journal Year: 2024, Volume and Issue: 31(9), P. 5255 - 5290

Published: Sept. 6, 2024

Artificial intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning natural language processing, their applications HNC. The integration of with imaging techniques, genomics, electronic health records explored, emphasizing its role early detection, biomarker discovery, planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, real-time monitoring systems are poised to further advance field. Addressing these fostering among experts, clinicians, researchers crucial developing equitable effective applications. future HNC holds significant promise, offering potential breakthroughs diagnostics, personalized therapies, improved patient outcomes.

Language: Английский

---

Large language model use in clinical oncology

npj Precision Oncology, Journal Year: 2024, Volume and Issue: 8(1)

Published: Oct. 23, 2024

Large language models (LLMs) are undergoing intensive research for various healthcare domains. This systematic review and meta-analysis assesses current applications, methodologies, the performance of LLMs in clinical oncology. A mixed-methods approach was used to extract, summarize, compare methodological approaches outcomes. includes 34 studies. primarily evaluated on their ability answer oncologic questions across The highlights a significant variance, influenced by diverse methodologies evaluation criteria. Furthermore, differences inherent model capabilities, prompting strategies, oncological subdomains contribute heterogeneity. lack use standardized LLM-specific reporting protocols leads disparities, which must be addressed ensure comparability LLM ultimately leverage reliable integration technologies into practice.

Language: Английский

---

ReCARving the future: bridging CAR T-cell therapy gaps with synthetic biology, engineering, and economic insights

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Sept. 5, 2024

Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the treatment of hematologic malignancies, offering remarkable remission rates in otherwise refractory conditions. However, its expansion into broader oncological applications faces significant hurdles, including limited efficacy solid tumors, safety concerns related to toxicity, and logistical challenges manufacturing scalability. This review critically examines latest advancements aimed at overcoming these obstacles, highlighting innovations CAR engineering, novel targeting strategies, improvements delivery persistence within tumor microenvironment. We also discuss development allogeneic T cells as off-the-shelf therapies, strategies mitigate adverse effects, integration with other therapeutic modalities. comprehensive analysis underscores synergistic potential enhance safety, efficacy, accessibility providing a forward-looking perspective on their evolutionary trajectory cancer treatment.

Language: Английский

---

Use of Artificial Intelligence for Liver Diseases: A Survey from the EASL Congress 2024

JHEP Reports, Journal Year: 2024, Volume and Issue: 6(12), P. 101209 - 101209

Published: Sept. 6, 2024

Language: Английский

---

Einsatz der künstlichen Intelligenz in der Diagnostik und Therapie solider Tumoren

Deleted Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

---